Reads were aligned to the hg38 assembly using STAR (2.5.2b). The following alignment QC report was produced:
SRP033351_QC_RnaSeqReport.html
HTSeq (0.6.1) function htseq-count was used to count reads. Counts for all samples were concatenated into the following text file:
SRP033351_htseq_gene.txt
DESeq2 (1.18.1) was used for differential gene expression analaysis, based on the HTSeq counts matrix and the phenotype file provided. Normalized counts from DESeq2 are saved in the following text file:
SRP033351_counts_normalized_by_DESeq2.txt
Normalized counts are obtained from DESeq2 function estimateSizeFactors(), which divides counts by the geometric mean across samples; this function does not correct for read length. The normalization method is described in detail here: https://genomebiology.biomedcentral.com/articles/10.1186/gb-2010-11-10-r106
Differential gene expression analysis was done for all comparisons provided in the comparisons file. The following design was used:
design = ~ + Donor + Status
If desired, the design can be modified to include more independent variables. In addition to the partial results displayed in this report, the full set of DESeq2 results for each comparison was saved down in separate text files, with names of the form:
SRP033351_CASE_vs_CONTROL_DESeq2_results.txt
where CASE and CONTROL are pairs of conditions specified in the comparisons file.
Volcano plot (probes with a q-value <0.05 are present in red)
Genes were ranked by adjusted p-values.
Compute PCs and variance explained by the first 10 PCs
| PC | Proportion of Variance (%) | Cumulative Proportion of Variance (%) |
|---|---|---|
| PC1 | 50.32 | 50.32 |
| PC2 | 24.78 | 75.09 |
| PC3 | 14.48 | 89.57 |
| PC4 | 6.771 | 96.34 |
| PC5 | 2.523 | 98.87 |
| PC6 | 0.788 | 99.65 |
| PC7 | 0.346 | 100 |
| PC8 | 4.763e-29 | 100 |
PCA plots are generated using the first two principle components colored by known factors (e.g. Status, Tissue, or Donor)
Genes were ranked by pvalue. Counts have been normalized by sequencing depth, with pseudocount of 0.5 added to allow for log scale plotting, using DESeq2 function plotCounts().
Boxplots for user-defined favorite genes if they exist, and show DE results
Volcano plot (probes with a q-value <0.05 are present in red)
Genes were ranked by adjusted p-values.
Compute PCs and variance explained by the first 10 PCs
| PC | Proportion of Variance (%) | Cumulative Proportion of Variance (%) |
|---|---|---|
| PC1 | 45.79 | 45.79 |
| PC2 | 26.59 | 72.38 |
| PC3 | 14.57 | 86.95 |
| PC4 | 9.279 | 96.23 |
| PC5 | 2.044 | 98.28 |
| PC6 | 1.109 | 99.39 |
| PC7 | 0.6136 | 100 |
| PC8 | 2.916e-29 | 100 |
PCA plots are generated using the first two principle components colored by known factors (e.g. Status, Tissue, or Donor)
Genes were ranked by pvalue. Counts have been normalized by sequencing depth, with pseudocount of 0.5 added to allow for log scale plotting, using DESeq2 function plotCounts().
Boxplots for user-defined favorite genes if they exist, and show DE results
Volcano plot (probes with a q-value <0.05 are present in red)
Genes were ranked by adjusted p-values.
Compute PCs and variance explained by the first 10 PCs
| PC | Proportion of Variance (%) | Cumulative Proportion of Variance (%) |
|---|---|---|
| PC1 | 46.28 | 46.28 |
| PC2 | 24.3 | 70.58 |
| PC3 | 16.38 | 86.96 |
| PC4 | 9.871 | 96.83 |
| PC5 | 1.424 | 98.26 |
| PC6 | 0.9661 | 99.22 |
| PC7 | 0.7756 | 100 |
| PC8 | 5.418e-29 | 100 |
PCA plots are generated using the first two principle components colored by known factors (e.g. Status, Tissue, or Donor)
Genes were ranked by pvalue. Counts have been normalized by sequencing depth, with pseudocount of 0.5 added to allow for log scale plotting, using DESeq2 function plotCounts().
Boxplots for user-defined favorite genes if they exist, and show DE results
Counts have been normalized by estimated size factors using DESeq2. Obtain the count matrix using function DESeq2::counts.
The table shows p-values of house-keeping genes for each comparison. Generally, house-keeping gene expressions do not change significantly in different conditions.
R version 3.4.3 (2017-11-30)
Platform: x86_64-redhat-linux-gnu (64-bit)
locale: LC_CTYPE=en_US.UTF-8, LC_NUMERIC=C, LC_TIME=en_US.UTF-8, LC_COLLATE=en_US.UTF-8, LC_MONETARY=en_US.UTF-8, LC_MESSAGES=en_US.UTF-8, LC_PAPER=en_US.UTF-8, LC_NAME=C, LC_ADDRESS=C, LC_TELEPHONE=C, LC_MEASUREMENT=en_US.UTF-8 and LC_IDENTIFICATION=C
attached base packages: parallel, stats4, stats, graphics, grDevices, utils, datasets, methods and base
other attached packages: pander(v.0.6.1), biomaRt(v.2.34.2), tidyr(v.0.8.1), DT(v.0.4), DESeq2(v.1.18.1), SummarizedExperiment(v.1.8.1), DelayedArray(v.0.4.1), matrixStats(v.0.54.0), Biobase(v.2.38.0), GenomicRanges(v.1.30.3), GenomeInfoDb(v.1.14.0), IRanges(v.2.12.0), S4Vectors(v.0.16.0), BiocGenerics(v.0.24.0), viridis(v.0.5.0), viridisLite(v.0.3.0), ggplot2(v.3.0.0), genefilter(v.1.60.0), lattice(v.0.20-35), plyr(v.1.8.4), RColorBrewer(v.1.1-2), reshape2(v.1.4.3), gplots(v.3.0.1) and rmarkdown(v.1.9)
loaded via a namespace (and not attached): bitops(v.1.0-6), bit64(v.0.9-7), httr(v.1.3.1), progress(v.1.1.2), rprojroot(v.1.3-2), tools(v.3.4.3), backports(v.1.1.2), R6(v.2.2.2), rpart(v.4.1-11), KernSmooth(v.2.23-15), Hmisc(v.4.1-1), DBI(v.0.8), lazyeval(v.0.2.1), colorspace(v.1.3-2), nnet(v.7.3-12), withr(v.2.1.2), prettyunits(v.1.0.2), tidyselect(v.0.2.4), gridExtra(v.2.3), curl(v.3.1), bit(v.1.1-12), compiler(v.3.4.3), htmlTable(v.1.11.2), labeling(v.0.3), caTools(v.1.17.1), scales(v.1.0.0), checkmate(v.1.8.5), stringr(v.1.3.0), digest(v.0.6.16), foreign(v.0.8-69), XVector(v.0.18.0), base64enc(v.0.1-3), pkgconfig(v.2.0.2), htmltools(v.0.3.6), htmlwidgets(v.1.2), rlang(v.0.2.2), rstudioapi(v.0.7), RSQLite(v.2.0), shiny(v.1.1.0), bindr(v.0.1.1), jsonlite(v.1.5), crosstalk(v.1.0.0), BiocParallel(v.1.12.0), gtools(v.3.5.0), acepack(v.1.4.1), dplyr(v.0.7.6), RCurl(v.1.95-4.10), magrittr(v.1.5), GenomeInfoDbData(v.1.0.0), Formula(v.1.2-2), Matrix(v.1.2-12), Rcpp(v.0.12.18), munsell(v.0.5.0), stringi(v.1.2.3), yaml(v.2.1.18), zlibbioc(v.1.24.0), grid(v.3.4.3), blob(v.1.1.1), promises(v.1.0.1), gdata(v.2.18.0), splines(v.3.4.3), annotate(v.1.56.2), locfit(v.1.5-9.1), knitr(v.1.20), pillar(v.1.2.1), geneplotter(v.1.56.0), XML(v.3.98-1.10), glue(v.1.3.0), evaluate(v.0.10.1), latticeExtra(v.0.6-28), data.table(v.1.11.4), httpuv(v.1.4.3), gtable(v.0.2.0), purrr(v.0.2.5), assertthat(v.0.2.0), mime(v.0.5), xtable(v.1.8-2), later(v.0.7.3), survival(v.2.41-3), tibble(v.1.4.2), AnnotationDbi(v.1.40.0), memoise(v.1.1.0), bindrcpp(v.0.2.2) and cluster(v.2.0.6)